llm_callback_handler.py 3.4 KB

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  1. import logging
  2. import time
  3. from typing import Any, Dict, List, Union
  4. from langchain.callbacks.base import BaseCallbackHandler
  5. from langchain.schema import LLMResult, BaseMessage, BaseLanguageModel
  6. from core.callback_handler.entity.llm_message import LLMMessage
  7. from core.conversation_message_task import ConversationMessageTask, ConversationTaskStoppedException
  8. class LLMCallbackHandler(BaseCallbackHandler):
  9. raise_error: bool = True
  10. def __init__(self, llm: BaseLanguageModel,
  11. conversation_message_task: ConversationMessageTask):
  12. self.llm = llm
  13. self.llm_message = LLMMessage()
  14. self.start_at = None
  15. self.conversation_message_task = conversation_message_task
  16. @property
  17. def always_verbose(self) -> bool:
  18. """Whether to call verbose callbacks even if verbose is False."""
  19. return True
  20. def on_chat_model_start(
  21. self,
  22. serialized: Dict[str, Any],
  23. messages: List[List[BaseMessage]],
  24. **kwargs: Any
  25. ) -> Any:
  26. self.start_at = time.perf_counter()
  27. real_prompts = []
  28. for message in messages[0]:
  29. if message.type == 'human':
  30. role = 'user'
  31. elif message.type == 'ai':
  32. role = 'assistant'
  33. else:
  34. role = 'system'
  35. real_prompts.append({
  36. "role": role,
  37. "text": message.content
  38. })
  39. self.llm_message.prompt = real_prompts
  40. self.llm_message.prompt_tokens = self.llm.get_num_tokens_from_messages(messages[0])
  41. def on_llm_start(
  42. self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
  43. ) -> None:
  44. self.start_at = time.perf_counter()
  45. self.llm_message.prompt = [{
  46. "role": 'user',
  47. "text": prompts[0]
  48. }]
  49. self.llm_message.prompt_tokens = self.llm.get_num_tokens(prompts[0])
  50. def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
  51. end_at = time.perf_counter()
  52. self.llm_message.latency = end_at - self.start_at
  53. if not self.conversation_message_task.streaming:
  54. self.conversation_message_task.append_message_text(response.generations[0][0].text)
  55. self.llm_message.completion = response.generations[0][0].text
  56. self.llm_message.completion_tokens = self.llm.get_num_tokens(self.llm_message.completion)
  57. self.conversation_message_task.save_message(self.llm_message)
  58. def on_llm_new_token(self, token: str, **kwargs: Any) -> None:
  59. try:
  60. self.conversation_message_task.append_message_text(token)
  61. except ConversationTaskStoppedException as ex:
  62. self.on_llm_error(error=ex)
  63. raise ex
  64. self.llm_message.completion += token
  65. def on_llm_error(
  66. self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
  67. ) -> None:
  68. """Do nothing."""
  69. if isinstance(error, ConversationTaskStoppedException):
  70. if self.conversation_message_task.streaming:
  71. end_at = time.perf_counter()
  72. self.llm_message.latency = end_at - self.start_at
  73. self.llm_message.completion_tokens = self.llm.get_num_tokens(self.llm_message.completion)
  74. self.conversation_message_task.save_message(llm_message=self.llm_message, by_stopped=True)
  75. else:
  76. logging.error(error)